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Risorsa bibliografica obbligatoria
Risorsa bibliografica facoltativa
Scheda Riassuntiva
Anno Accademico 2019/2020
Tipo incarico Dottorato
Insegnamento 050674 - ADVANCED TOPICS IN ECONOMETRICS
Docente Mosconi Rocco Roberto
Cfu 5.00 Tipo insegnamento Monodisciplinare

Corso di Dottorato Da (compreso) A (escluso) Insegnamento
MI (1386) - INGEGNERIA GESTIONALE / MANAGEMENT ENGINEERINGAZZZZ050674 - ADVANCED TOPICS IN ECONOMETRICS

Programma dettagliato e risultati di apprendimento attesi

Selected Learning Goals: The Course mainly contributes to the following Programme Learning Goals:
- Ability of selecting, applying, and developing research methods in engineering and social sciences (LG2)

Course Aims:  The course illustrates, based on a hands on approach, two econometric methodologies frequently used in state of the art empirical research in the fields of economics, management, and industrial engineering. Specifically the course covers the analysis of panel data sets, i.e. datasets where several individuals are observed over time, and Structural Equation Models (SEM), a flexible approach to modeling statistical data which encompasses a broad array of models from linear regression to measurement models to simultaneous equations, including confirmatory factor analysis and other techniques. The methods are illustrated using Stata.

Intended Learning Outcomes (ILOs): At the end of the course, the students are expected to be able to:
- Match and relate theories and methods (LO2.1)
- Apply mainstream research methods (LO2.2)
- Experiment extant methods in new settings (LO2.3)

Pedagogical methods/tools: Lectures, Presentation of Cases, Discussions, Individual/team assignment


Note Sulla Modalità di valutazione

Assessment methods: Paper (one or two authors) consisting of an application of at least one of the methodologies presented in the course (panel or SEM) to address appropriate research questions proposed by the student. Structure of the paper: 1) Introduction, clearly stating the research question(s) and summarizing the relevant theory 2) Description of the available dataset, using appropriate summary statistics 3) Illustration of the proposed econometric model 4) Results and conclusions. The papers have to be prepared and sent to all course participants one week before the presentation. Active participation to the presentations is encouraged.

Evaluation: Paper, 100% of the overall grade, equally weighting ILO2.1, ILO2.2 and ILO2.3. In case of joint paper, the individual contribution has to be declared in the first footnote and emphasized in the presentation: in fact, 50% of the mark will be individual, based on the individual contribution, quality of the individual presentation, individual interaction during the course and the presentation.


Intervallo di svolgimento dell'attività didattica
Data inizio
Data termine

Calendario testuale dell'attività didattica

Planning: The course is organized in 9 sessions of 3 hours each:

SESSION 1, 10/2/2020, 14.00-17.00: Introduction to panel data models; brush up on ordinary least squares, generalized least squares, instrumental variables, generalized method of moments
SESSION 2, 11/2/2020, 10.00-13.00: Fixed Effects models (Testing the Significance of the Group Effects, The Within- and Between-Groups Estimators, Fixed Time and Group Effects, Unbalanced Panels and Fixed Effects).
SESSION 3, 11/2/2020, 14.00-17.00: Random Effects models (Generalized Least Squares, Feasible Generalized Least Squares when the variance covariance matrix is Unknown; Testing for Random Effects; Hausman’s Specification Test for the Random Effects).
SESSION 4, 12/2/2020, 10.00-13.00: Dynamic Panel Data Models
SESSION 5, 12/2/2020, 14.00-17.00: The basic building blocks of SEM models (univariate and multivariate regression, confirmatory factor analysis, path diagrams)
SESSION 6, 13/2/2020, 10.00-13.00: Illustration of simultaneity bias: estimating demand/supply systems as an illustration of identification issues
SESSION 7, 13/2/2020, 14.00-17.00: Dealing with unobservable variables in SEM: measurement blocks; identification issues
SESSION 8, 14/2/2020, 14.00-17.00: Dealing with binary, categorical, ordinal variables in SEM: Generalized SEM
SESSION 9, 18/3/2020, 14.00-17.00: Discussion of the papers prepared by the students


Bibliografia
Risorsa bibliografica obbligatoriaGreene, W.H., Econometric Analysis
Note:

Selected chapters

Risorsa bibliografica obbligatoriaKline, R.B., Principles and Practice of Structural Equation Modeling

Software utilizzato
Nessun software richiesto

Mix Forme Didattiche
Tipo Forma Didattica Ore didattiche
lezione
24.0
esercitazione
3.0
laboratorio informatico
0.0
laboratorio sperimentale
0.0
progetto
3.0
laboratorio di progetto
0.0

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese
Disponibilità di materiale didattico/slides in lingua inglese
Disponibilità di libri di testo/bibliografia in lingua inglese
Possibilità di sostenere l'esame in lingua inglese
Disponibilità di supporto didattico in lingua inglese

Note Docente
schedaincarico v. 1.6.9 / 1.6.9
Area Servizi ICT
29/11/2021